{"id":"W4392214886","doi":"10.1016/j.ijggc.2024.104100","title":"Effective microseismic monitoring of the Quest CCS site, Alberta, Canada","year":2024,"lang":"en","type":"article","venue":"International journal of greenhouse gas control","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Shell (Canada)","funders":"Norges Forskningsråd; Agence de l'Environnement et de la Maîtrise de l'Energie; Agence de la transition écologique; Emissions Reduction Alberta","keywords":"Microseism; Caprock; Plume; Petroleum engineering; Reliability (semiconductor); Geology; Environmental science; Mining engineering; Seismology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002584675,0.0001065782,0.0001921888,0.0001040853,0.00006647842,0.00006597047,0.000909949,0.00003673911,0.000005298712],"category_scores_gemma":[0.0002059045,0.00007111683,0.0001512721,0.0001222119,0.00006585586,0.0002562286,0.0001062047,0.0002618625,0.00000496546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321706,"about_ca_system_score_gemma":0.000441634,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07103764,"about_ca_topic_score_gemma":0.04753416,"domain_scores_codex":[0.998856,0.0001000609,0.0003404936,0.0001270005,0.0004362964,0.0001401307],"domain_scores_gemma":[0.9984855,0.0006996747,0.0002116256,0.000146181,0.0004061037,0.00005092112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005973488,0.0003359888,0.6059781,0.00009352069,0.007534571,0.002517266,0.007976688,0.009515212,0.01282123,0.01802681,0.02114116,0.3134621],"study_design_scores_gemma":[0.004973485,0.0006479499,0.858911,0.001487134,0.0002665067,0.003318183,0.0002058018,0.01896853,0.02370226,0.005328595,0.08160114,0.0005894096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9499208,0.002455681,0.02109747,0.01528446,0.01081158,0.0001362235,0.00001516743,0.00001868157,0.0002599836],"genre_scores_gemma":[0.9984717,0.00005084935,0.0002691376,0.0005175267,0.0005103828,0.000002758736,1.263574e-7,0.0000070647,0.0001704006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3128727,"threshold_uncertainty_score":0.9698458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004241446975981664,"score_gpt":0.2208858539288895,"score_spread":0.2166444069529079,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}